Literature DB >> 12773500

Temporally irregular mnemonic persistent activity in prefrontal neurons of monkeys during a delayed response task.

Albert Compte1, Christos Constantinidis, Jesper Tegner, Sridhar Raghavachari, Matthew V Chafee, Patricia S Goldman-Rakic, Xiao-Jing Wang.   

Abstract

An important question in neuroscience is whether and how temporal patterns and fluctuations in neuronal spike trains contribute to information processing in the cortex. We have addressed this issue in the memory-related circuits of the prefrontal cortex by analyzing spike trains from a database of 229 neurons recorded in the dorsolateral prefrontal cortex of 4 macaque monkeys during the performance of an oculomotor delayed-response task. For each task epoch, we have estimated their power spectrum together with interspike interval histograms and autocorrelograms. We find that 1). the properties of most (about 60%) neurons approximated the characteristics of a Poisson process. For about 25% of cells, with characteristics typical of interneurons, the power spectrum showed a trough at low frequencies (<20 Hz) and the autocorrelogram a dip near zero time lag. About 15% of neurons had a peak at <20 Hz in the power spectrum, associated with the burstiness of the spike train; 2). a small but significant task dependency of spike-train temporal structure: delay responses to preferred locations were characterized not only by elevated firing, but also by suppressed power at low (<20 Hz) frequencies; and 3). the variability of interspike intervals is typically higher during the mnemonic delay period than during the fixation period, regardless of the remembered cue. The high irregularity of neural persistent activity during the delay period is likely to be a characteristic signature of recurrent prefrontal network dynamics underlying working memory.

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Year:  2003        PMID: 12773500     DOI: 10.1152/jn.00949.2002

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  91 in total

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9.  Attractor Dynamics in Networks with Learning Rules Inferred from In Vivo Data.

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10.  Beyond Poisson: increased spike-time regularity across primate parietal cortex.

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Journal:  Neuron       Date:  2009-05-14       Impact factor: 17.173

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